One problem of computer-aided imaging systems used today can be considered to be that an extremely large volume of data needs to be managed. The increased high-sensitivity and time resolution of the modalities used means that the number of image data items acquired there is continually rising, so that in sectional image diagnosis and in the case of multi-row CTs and functional NMR tomography, for example, the volume of data generated has continually increased in recent years. For certain examinations, this results in a data volume in the two-digit gigabyte range.
The significantly increased number of data items to be managed results in new problem scenarios in data management and when transmitting the data from the data source (that is to say the respective imaging modality) to one or more entities for the purpose of processing. Data system bottlenecks arise particularly when transmitting the image data via networks, e.g. via a WAN (wide area network) or via a LAN (local area network), and distributing them from the modality to analysis workstations and to the image archive, e.g. to a PACS system (picture archiving and communication system).
The increased volume of data means that the image data in a regular PACS environment can no longer readily be distributed to further entities or nodes in real time. The result is disadvantageously a “backlog”, so to speak, at the data source, that is to say at the respective modality. This produces delays before the image data are available on the analysis workstation. In addition, delays arise before the image data can be safely archived on the modality following an acquisition. Previous systems are therefore found to be lacking and, in the worst case, there may even be a loss of data if the volume of data exceeds the available capacity.
To counteract the aforementioned problems, different approaches have been developed in the prior art to date.
Firstly, provision is made for some of the image data to be transmitted at different times when network load is low. Although this approach makes it possible to prevent the image data which are to be transmitted from being transported at peak network load times, it does not allow the data to be reduced and transmitted more quickly.
In addition, what is known as rule-based routing and prefetching of image data is known, where image data are purposefully sent to network nodes for further processing. In this context, purposeful sending is based on organizational structures, such as parameters relating to the department or the personnel, and on other organizational procedures, such as appointments, meetings etc.
In addition, approaches are known which provide image data compression and what is known as progressive loading. This approach involves compressed image data being transmitted at reduced resolution or in reduced quality. If required, further image data are subsequently loaded at a later time until the original resolution and the desired image quality has been achieved. Although this approach allows the volume of data to be reduced, the image data are not sent for purposeful distribution and association with particular nodes for the purpose of further processing.
Hence, this approach involves all of the image data, whether compressed or uncompressed, being sent to the relevant further processing nodes, when a subset of the data would sometimes have sufficed. When different examination data are repeatedly requested from analysis workstations, this approach results in a relatively high network load. Another drawback of this approach can be considered to be that in principle there is the risk of a loss of data, since a safe archiving option on the modality (in contrast to PACS archives) is normally not possible.
A further approach which may be cited from the prior art is the use of a central image processing server, in which central postprocessing (particularly rendering) of volume data records is carried out on a powerful image processing server, for which 3D graphic accelerators are normally used. An advantage of this approach can be considered to be that the requesting entity (the client) does not require the whole 3D data record, as would be the case for local calculation of the image display.
In this connection, reference can be made to the two American patent specifications U.S. Pat. No. 6,683,933 B2 and US 2003/0156745 A1, where provision is made for the data to be sent centrally to an image processing server or to an image manager (PACS). In the case of this method, the data volume for transmitting the rendered image data is significantly reduced.
A drawback of this approach is that the large volumes of data which are generated on the modalities must first of all be transmitted to a central node. The necessary full transmission of the large volumes of data to a central entity means that capacity bottlenecks often arise during transmission. Distribution of the data volumes over local nodes is not considered here.